jreisner/sparseBiclustering: Biclustering with Missing Data
Version 0.1.0

Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since biclustering is said to be NP-hard, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values.

Getting started

Package details

AuthorJohn Reisner, Hieu Pham, Jing Li
MaintainerJohn Reisner <[email protected]>
LicenseMIT + file LICENSE
Version0.1.0
URL http://github.com/jreisner/biclustermd
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("jreisner/sparseBiclustering")
jreisner/sparseBiclustering documentation built on Oct. 12, 2018, 2:01 p.m.